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Ten Tips for Maintaining Digital Image Quality

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Ten Tips for Maintaining Digital Image Quality © 2007, IS&T: The Society for Imaging Science and Technology Ten Tips for Maintaining Digital Image Quality Peter D. Burns and Don Williams, Eastman Kodak Company, Rochester NY by system image quality requirements, physical imaging Abstract parameters provide the link to technology selection and The development of digital collections has benefited from interpretation. For example, image sharpness is a visual both the technology and price-volume advantages of the wider impression; lens MTF is a physical imaging parameter related to digital imaging markets. With the advent of web-based delivery, image sharpness, and to optical design and adjustment (the standard file formats, and metadata, however, have come a host of Technology Variables, of Ref. 3). technology related choices and concerns about variability and compatibility. We suggest ten simple principles that can be used to 3. Sampling is Not Resolution increase utility and reduce variation of the digital image content Image sampling indicates the sampling interval between for most collection projects. pixels on a particular plane in the scene (camera), or on the object (scanner). It is often referred to in pixels/mm or pixels/inch. Image Introduction resolution, or limiting resolution, has its roots in continuous optical The following are a collection of tips aimed at providing imaging systems. Resolution refers to the ability of an imaging guidance for those responsible for establishing and maintaining the component or system to distinguish finely spaced details. For imaging performance during image conversion projects. Each of (sampled) digital images, the sampling rate (or mega-pixel rating the suggestions is well understood (and often debated) in the for a camera) sets an upper limit for the capture of image detail. technical imaging community, but not always clear to the wider The image sensor size and architecture usually determine the group of clientele in museums, libraries, and similar institutions. image sampling, while other components also influence the Presented as short recommendations, they can form the basis for delivered image sharpness and resolution. questions that project managers can ask their technical staff and To understand this, consider a digital camera with a lens that imaging service providers. is well focused on a subject. After capturing the scene, the lens focus position is changed so the subject is not well focused. If we 1. Scan but Verify compare the two image files, they will have same image sampling Perhaps the most important function to include in a digitizing (and number of pixels), but the second digital image will appear workflow is a method and practice of verifying delivered imaging less sharp when viewed on a computer monitor or print. The performance. This applies whether comparing different scanners, second image will have lower resolution. or selecting service providers. Is the requested sampling rate (i.e. A well-established method for evaluating camera or scanner pixels per inch) actually being delivered? Is the optical resolution resolution was developed for the standard, ISO 12233. Originally consistent with the sampling rate? To what extent does the color developed for digital cameras, the method has been applied to film encoding differ from a desired specification? All of these questions and print scanners, and CRT displays.4 Figure 1 shows the results call for establishing measurable goals for the imaging unit, when the above method was applied to this digital camera focus whether in-house or subcontracted. More importantly they serve as experiment. The resulting spatial Frequency Response (SFR) is a the basis for both real-time production control and acceptance function of spatial frequency. The lower dashed curve indicates the auditing; 1,2 in other words, good quality control. Remember, just effective loss of image detail information, e.g. limiting resolution, because content is digital does not make it error free. due to optical defocus. Performance verification measures can also be adapted to improvement initiatives. Once a performance measurement system is in place, however, questions will naturally arise as to the interpretation of results and possible corrective actions. The following suggestions and observations are intended to help in this area. 2. Imaging Performance is not Image Quality A common objective for image acquisition in cultural heritage projects is to produce high quality images. As a goal this statement may be adequate, but it is generally not helpful when evaluating how well an imaging function is being accomplished, and how to improve the system. In addition, overall image quality is usually understood to mean the visual impression, and this can have many components such as sharpness and colorfulness, and personal preferences. In this report we refer to imaging Figure 1: SFR measurement results for the digital camera with two lens performance as described by physical imaging parameters.3 While focus positions the particular acceptable levels of performance will usually be set Proc. IS&T Archiving Conf., pg. 16-22, IS&T, 2007 4. Single Stimulus Visual Assessments of Color, This can be easily understood based on the SFR plot, Tone Can be Unreliable computed using an edge feature in each digital image. It has been Work in the imaging field for some time and one is bound to suggested that the spatial frequency at which the SFR is reduced to see examples of how easily we can be fooled into perceiving 0.1 (10%) serves as a measure of limiting resolution. The arrows significant color and brightness differences in natural scenes of indicate these (relative) values, which are consistent with the what are otherwise physically identical stimuli. Most of these corresponding clock faces. A different measure, acutance, however illusions are due to the complex spatio-temporal adaptation has been used to predict image sharpness. This integrated responses of the human visual system.5 An example is shown in frequency-weighted measure7 will be a function of viewing Fig. 2 from a collection 6 that could provide hours of rainy-day distance. When viewed as presented here, however, the higher fun. response at the lower frequencies indicates a higher sharpness for the upper picture. Figure 2: Example from Ref. 6. While the center regions of the top row are perceived as having different contrasts, masking the surround (bottom row) reveals they are of identical. While these effects are real in terms of perceived brightness, they are misleading when interpreted as radiometric differences. Viewing environment, observer variability and preferences are major factors. For system evaluation, dual stimuli visual assessments under the same viewing conditions are advisable. To a lesser extent visual evaluations of image microstructure should also be treated cautiously. For example, visual resolution judgments can be driven by feature contrast: the higher the high sharpness, low resolution contrast, the higher the resolution rating. Another problem, well 1.0 known in traditional photography, is that the size, shape and extent low sharpness, high resolution of the target features can bias image resolution evaluations. When using the classical bar target patterns for limiting resolution, the SFR viewer has a priori knowledge of the number of bars to be 0.5 detected. This can bias the evaluation. Results can also vary with length of the bar, where a longer length feature can result in a higher estimated resolution value. While on the topic of limiting resolution, we also consider 0.1 overall image sharpness. Figure 3 shows two versions of a railway 0 station scene. The upper picture resulted from applying digital 0.25 0.5 sharpening filter to an unsharp digital image. The lower version Frequency , cy/pixel was captured with a well-focused camera without digital sharpening. The limiting resolution, as illustrated by the expanded Figure 3: Upper picture is for unsharp capture followed by digital clock face, is higher for the lower picture, as we might expect. The sharpening. The lower is for a well-focused capture without sharpening. The graph shows the corresponding SFR results based on analysis of digitally sharpened version, however, gives the impression of a an edge feature in each picture. sharper image. 5. Visual Assessments of Spatial Artifacts Can be resolution limit Reliable optical resolution due to poor A good skill for detecting ill-behaved image performance of limit CFA scanned images is visual literacy. An abridged definition, taken reconstruction from Brill, Kim and Branch8 and adapted for the evaluation of digital image performance is, Visual Literacy: Acquired competencies for interpreting and composing visible messages. A visually literate person is able to interpret visible objects to detect unnatural or unexpected behavior, and identify possible underlying sources of performance variation. As indicated in the previous section, interpretation of single stimulus visual assessments for color and tone reproduction evaluation can be unreliable. Doing so for spatial artifacts of both signals and noise, however, can be dependable and valuable. This is because spatial and noise artifacts associated with digital imaging often occur in relatively local regions. When displayed, several suspect regions are within the same visual field, and many variations, e.g. directional differences, in characteristics can easily be detected. In effect, several stimuli can be presented to the eye and evaluated nearly simultaneously.
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